A new initiative dedicated to the benchmarking of coupled surface-atmosphereSecond announcement
RAMI4ATM is a new initiative dedicated to the benchmarking of coupled surface-atmosphere radiative transfer models. RAMI4ATM will thus expand RAdiation transfer Model Intercomparison (RAMI) to the simulation of satellite observations. Compared to current benchmarks, the major difference is that RAMI4ATM will account for atmospheric radiative effects occurring between the surface and the simulated signal reaching a given spaceborne radiometer. Copernicus Sentinel-2A/MSI instrument has been chosen for that purpose. Models participating in RAMI-atmosphere should support the simulation radiative processes at the surface, in the atmosphere and account for the radiative coupling between the two.
Over the past decades, many radiative transfer models have been developed and are widely used for e.g. vicarious calibration and lookup table generation for atmospheric correction. Many of these models ship atmospheric property databases. Subcomponents of these models have been extensively tested in ideal conditions but so far, no long-term initiative similar to RAMI has been undertaken to systematically compare models when they are used to simulate actual remote sensing observations. The uncertainties of these models has not been clearly assessed in realistic usage conditions when supporting typical Earth Observation applications.
Similarly to RAMI-1, the primary goal of RAMI4ATM will be to document the variability between coupled surface-atmosphere models when run under well-controlled, but realistic, conditions. Surface properties will be defined by the simple homogeneous scenes as defined in previous RAMI phases.
This new phase is oriented toward the support of calibration and validation activities relying on the use of radiative transfer models for the simulation of satellite observations in the visible, near and shortwave infrared spectral regions. It is therefore primarily directed at model users involved in calibration and validation activities. Participation from model developers is however also welcome. During this phase, special care will be taken to provide a computation priority order so that smaller teams can also compare their results efficiently.
RAMI4ATM will cover the following cases:
The expected outcome of this exercise is as follows:
RAMI4ATM will be publicly opened in April 2022.
Pre-registration is highly encouraged sending an email here with the following information:
